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Unbalanced bidding can seriously imposed the government from obtaining the best value for the taxpayers' money in public procurement since it increases the owner's cost and decreases the fairness of the competitive bidding process. How to detect an unbalanced bid is a challenging task faced by theoretical researchers and practical actors. This study aims to develop an identification method of unbalanced bidding in the construction industry.

The identification of unbalanced bidding is considered as a multi-criteria decision-making (MCDM) problem. A data-driven unit price database from the historical bidding document is built to present the reference unit prices as benchmarks. According to the proposed extended TOPSIS method, the data-driven unit price is chosen as the positive ideal solution, and the unit price that has the furthest absolute distance measure as the negative ideal solution. The concept of relative distance is introduced to measure the distances between positive and negative ideal solutions and each bidding unit price. The unbalanced bidding degree is ranked by means of relative distance.

The proposed model can be used for the quantitative evaluation of unbalanced bidding from a decision-making perspective. The identification process is developed according to the decision-making process. The finding shows that the model will support owners to efficiently and effectively identify unbalanced bidding in the bid evaluation stage.

The data-driven reference unit prices improve the accuracy of the benchmark to evaluate the unbalanced bidding. The extended TOPSIS model is applied to identify unbalanced bidding; the owners can undertake objective decision-making to identify and prevent unbalanced bidding at the stage of procurement.

The purpose of this paper is to introduce a quantitative method for assisting contractors to select appropriate projects for bidding by considering multiple attributes and integrating decision group member opinions.

The fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method is used to help contractors make decision on project selection and the linguistic terms are defined for representing the triangular fuzzy numbers for ratings of alternatives and weights of criteria.

The selection of appropriate projects for bidding is a multiple attribute group decision‐making exercise. In a real decision process, there are many uncertainties and ambiguities, and time limitations mean that decision makers cannot always make precise judgments. The numerical example demonstrates that the fuzzy TOPSIS approach can be used to simulate the decision process in project selection, and the results provide contractors with valuable insight into the project selection problem.

Selecting appropriate projects for bidding is to use a contractor's limited resources more efficiently and increase the probability of winning contracts. Therefore, there is a need for a quantitative method to help contractors make better decision on project selection. That leads to the formulation of this paper. The fuzzy TOPSIS method can assist contractors to make better decisions in bidding.

This study aims to investigate and ranks the critical factors influencing the bid or no-bid decision and their importance for the indigenous small building contractors within the Tanzanian construction industry.

An interpretivist epistemological design was adopted to extensively manually review and search extant literature on bid or no-bid decision-making criteria. A total of 30 most common bid or no-bid decision-making criteria were identified. These were included in a questionnaire survey data collection instrument. The survey was distributed to 40 small indigenous (local) building contractors in Dar es Salaam, Tanzania. In total, 33 responses were received. Response data was subjected to both descriptive and inferential statistics.

The results show a disparity of ranking of the 30 bid/no-bid criteria factors among the two grades of small contractors, with 11 factors having statistically significant differences (p = < 0.05). Based on the overall sample, the most highly ranked seven factors in ascending order were: availability of capital; financial capacity of the client; project size; profitability; project type; need of work; and current workload. The following were the least ranked: tax liability; the degree of safety; availability of other projects; availability of labor; bidding document price; and uncertainty because of weather conditions. Availability of capital and financial capacity of the client were jointly ranked as the most important by Class VI contractors. In comparison, availability of capital and need of study were rated highly for Class VII contractors.

The sample consisted of indigenous small building contractors in one industry operating in Tanzania only and did not include the perceptions of the foreign contractors based in Dar es Salaam. Future studies are required to expand the current research and investigate this specific aspect further.

The identified “bid/no-bid criteria” information will allow indigenous small building contractors to enhance the efficiency and effectiveness of their bidding decision-making process. Emergent findings will enable said contractors to: better fit into the competitive construction business environment; increase their awareness of existing decision-making practices; and develop appropriate strategies for evaluation of opportunities encountered. Cumulatively, these findings benefit small indigenous building contractors by increasing their understanding of the factors influencing bid decision.

The study represents the first empirical study in Tanzania on the critical factors influencing the bid or no-bid decision among the indigenous small building contractors, which face fierce competition from foreign contractors.

Decisions by construction contractors to bid (or not to bid) require the thorough assessment and evaluation of factors relevant to the decision, as well as the quantification of their combined impact, to produce successful bid/no-bid decisions. The purpose of this study is to present a fuzzy fault tree model to assist construction contractors to more efficiently bid for future projects.

The proposed model consist of two stages: first, identification of the factors that affect bidding decision using a questionnaire survey after an extensive literature review, and second, usage of the identified factors to build a fuzzy fault tree model to simulate the bidding decision.

A list of 15 factors that affect bid/no-bid decisions was identified. Analysis of factors revealed that the highest-ranking factors were related to financial aspects of the project. A case study is presented to demonstrate the capabilities of the model, and a fuzzy important analysis is performed on the basic events to demonstrate the differences between three contractors’ bid/no-bid decisions. The results reveal that there is variation between the decisions of each contractor based on their willingness to participate. Besides, the influence of evaluation factors on the final decision for each contractor is different.

The study contributes to the body of knowledge on tendering and bidding practices. The proposed model incorporated the fuzzy set theory, which suits human subjectivity. The proposed methodology overcomes the limitations of previous models as it can, using the linear pool opinion principle, combine and weigh the evaluations of multiple experts. In addition, the model is convenient for situations where historical data are not available.

Factors affecting bid/no-bid decisions of international projects are more complex than those of domestic projects. The purpose of this paper is to identify and rank decision factors considered by variously sized Chinese international contractors (CICs) and categorize those groups of factors important to experienced practitioners.

The analysis of factors identified by a literature review is conducted based on data derived from questionnaire results received from 119 CIC project and bidding managers. The relative importance of factors is measured by mean value and standard deviation. The discrepancy in rank and importance value perceived by variously sized CICs are explored by ranking disparity analysis, non-parametric test and Spearman’s rank correlation coefficient test. Finally, factor analysis is used to categorize the underlying groups of factors considered by CICs.

In sum, 41 factors are identified through the literature review as having an impact on the bid decision. Significant disparities in ranking and importance are found in several factors, which partially affect the consistency of the ranking of factors perceived between large and small-medium CICs. Ultimately, nine major factors are identified as impacting the bidding decision, with “contractor’s capability” and “country risk of the host country,” being the most important.

The weight of a factor considered in a decision varies across contractors as a function of contractor size. Whether using models or subjective judgment in making decisions, it is beneficial to fully understand the main groups of factors influencing the decision. Vulnerability to country risk emerges as the first criterion accessed in the bid decision.

A comprehensive set of factors is established for CICs, including both general factors common to domestic projects, and international factors unique to international projects. All factors are grouped by inferential analysis from the perspective of contractors, which reveals the underlying mechanism of the bid decision-making process. While the data were collected from CICs, the methodology in exploring factors, along with implications, is determined to be applicable internationally.

The acknowledged mode of securing work by contractors is through the bidding process. However, the bidding decisions undertaken by some indigenous contractors in developing countries are fraught with challenges that often engender bidding practices (such as collusion through price fixing and intentional lower bidding) and threaten business survival. Therefore, in the quest to better understand these challenges and viable advocate solutions for overcoming them, this paper aims to identify the key challenges impacting the bid decision process by small indigenous building contractors in Dar es Salaam, Tanzania, and establish the strength of their relationship between the pairs of key challenges.

A comprehensive literature review was conducted to identify nine challenges impacting the bid decision of indigenous building contractors in Tanzania, which were used to design a questionnaire survey. Data collected were analysed using descriptive statistics, mean score, inferential statistics (One sample t-tests), Kendall’s concordance and correlation analysis.

Challenges identified from a literature review were empirically tested using survey responses accrued from 33 participating small indigenous building contractors in Dar es Salaam, Tanzania. The findings illustrate that lack of liquidity, profit returns, lack of equipment, lack of experience of several works and procurement procedures are perceived as being the five most critical challenges. Project location, site accessibility and lack of labour were least critical. The major finding from the correlation analysis was the existence of the strong and positive correlation between “project location” and “site accessibility”.

The study is limited by its sample and geographical settings which focussed and confined the results on one country, Tanzania. However, the findings can be considered as important for other developing countries wishing to gain insights into the challenges impacting bid decisions.

Measures for addressing the identified challenges impacting the bidding decisions of the indigenous small building contractors would be undertaken. The findings will enable contractors to not only reconcile the challenges with the industry and in so doing benefit both themselves and the clients but also enable them to be better prepared to deliver contractual obligations and generate socio-economic wealth. Government and policymakers will also be able to appropriately develop macro interventions for managing these challenges, which could be custom-tailored to indigenous small contractors. Finally, improving the ability of local firms to compete in the construction industry has been recognised as having the potential of advancing socio-economic development within the comity of developing countries.

The study enhances government, client and practitioners’ understanding of the challenges affecting the bidding practices among the indigenous building contractors in Tanzania. This area of investigation has previously been under explored particularly sub-Saharan Africa.

Describes a model for adapting successful bidding strategies, placing it in the context of a company's overall structure and competitive strategy. Lists the benefits of the decision system approach, revealing it to be a useful tool in a management information and control system.

For large projects, project segmentation and planning the size of contract packages in construction bids is a complex and critical issue. Due to the nature of construction projects, which frequently have large budgets, long durations and many activities with complex procedures, project segmentation involves complicated decision-making. To fill this gap, this study aims to develop an integrated model for planning project segmentation.

The proposed model integrates a simulation and multiple attribute decision-making method. The simulation is used to evaluate the bidding outcome of various project segmentations. The owner can then determine the bid-price behavior of contractors in response to varying work package sizes. The multiple attribute decision-making method is used to select the optimal segmentation solution from the simulated scenarios.

The proposed model is applied to a large road preservation project in Indonesia and incorporates bid participants and market conditions. The model provides seven scenarios for segmentation. The range of scenarios captures increasing competitiveness in the construction with the average bid price becoming gradually more beneficial for the owner. The model also utilizes a multiple attribute decision-making method to select the optimum scenario for the owner.

This study presents an applicable model for project segmentation that is useful for both project owners and contractors. By utilizing the proposed model, a project owner can segment a large project into smaller contract packages to create improved project pricing.

The purpose of this paper is to identify and rank the factors that affect the bid/no bid decision according to their relative importance from the perspective of the contracting parties operating in the Gaza Strip, Palestine.

The objectives of this research were investigated through a postal questionnaire, which covered a randomly selected sample of 63 contractors, 29 clients and 13 consultants operating in the construction industry in the Gaza strip. The questionnaire was structured based on related literature, the pilot study and actual factors affecting bidders' decisions to bid or not that arise from special conditions in the Gaza Strip. A total of 78 factors that affect the bid/no bid decision were identified. These factors were then ranked according to their relative importance to contracting parties operating in the Gaza Strip, Palestine.

The results illustrate that the financial capability of the contractors, the financial capability of the clients, the financial values of the project, the due date of the payments, the availability of construction raw materials in local markets, and the stability of the construction industry were the most critical factors affecting the bid/no bid decision, as agreed by all respondents.

The paper provides supportive practical solutions for contractors, clients and consultants to enhance and improve bidding decisions. It is recommended that clients and consultants consider the financial capabilities, technical capabilities and staff competencies of the contractors during the awarding stage, and not simply focus on the lowest bid.

The normative literature suggests that there are more than seventy decision factors that contractors must consider if they intend to success in their bid and projects. In addition, such factors have been grouped in relation to project characteristics, client attributes, contractors' business administration and external factors. The extant literature suggests that the relationships between many of the bid decision factors are orthogonal and may not explain how bid-decisions shape project outcomes.

This knowledge gap has stagnated research in this area. Building on findings of recent studies, this study unbundles bid decision themes by analysing key factors amongst contractors' administrative characteristics. In addition, the study determines intrinsic predictive correlation between the sub-themes. A total of 17 variables were listed in a structured questionnaire survey and presented to participants recruited through purposive snowballing. In total, 50 responses were received and formed the basis of descriptive and inferential statistical analyses.

The study found that the 17 factors are significant in bid decisions and consequently in bid successes. However, the explanatory variables attached to the themes are most efficient if categorised into six sub-themes. These are contractor's administration depth, strategic direction, commercial intention and own market advantage, resources, experience as well as openness to technology imposed by new projects. Furthermore, four theoretical positions are significant. Contractors bid for projects strategically; they are less reliant on their resource capabilities in bid decisions; every bid decision aligns with a risk strategy, and financial stability enables them to establish appropriate risk mitigation arrangements that could ensure project success.

These findings provide some support for the conceptual premise that bid decisions need to be rational, considered and strategically contribute to project outcomes.